from sklearn import tree
from random import random
from ImportCsv import importcsv
import numpy as np
# Load data
rowData = importcsv("../spambase.data")
data = []
for line in rowData:
listLine = []
for value in line:
listLine.append(float(value))
data.append(listLine)
#print(data[0])
#print(len(data))
#### Specific fields####
usedData = []
usedValue = []
usedData1 = []
usedValue1 = []
for line in data:
listLine = []
listLine1 = []
for k in range(len(line)):
#if k in [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, 19, 20, 21, 22, 23, 46, 51, 52, 53]:
if k in [
0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, 19, 20,
21, 22, 23, 37, 46, 51, 52, 53
listNoPb = []
clsf1 = AdaBoostClassifier(n_estimators=200)
#clsf2 = MLPClassifier()
clsf2 = MLPClassifier(verbose=0, random_state=0, max_iter=max_iter, **param)
clsf3 = KNeighborsClassifier(n_neighbors=nbNeighbors, weights=weightValue)
clsf4 = tree.DecisionTreeClassifier()
clsf5 = SVC(kernel="linear", C=0.2)
tot = 0
totCancelled = 0
for tour in range(nbTurns):
print(tour)
# Load data
rowData = importcsv(pathFile)
data = []
for line in rowData:
listLine = []
for value in line:
listLine.append(float(value))
data.append(listLine)
usedData = []
usedValue = []
for line in data:
listLine = []
for k in range(len(line)):
if k not in [27, 28, 31, 57, 3, 30, 32, 36, 39, 40, 46, 47]:
listLine.append(line[k])
usedValue.append(line[-1])
